Computational and Experimental Studies of Protein Structure and Design

蛋白质结构和设计的计算和实验研究

• 批准号: 10330495
• 负责人: Bruce R. Donald
• 金额: $ 52.48万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-02-01 至 2027-01-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10330495
• 关键词: 3-Dimensional; Algorithm Design; Algorithmic Software; Algorithms; Antibodies; Antigens; Area; Binding; Biochemical; Biological; Cells; Combinatorial Optimization; Computational Geometry; Computer Models; Computer software; Computing Methodologies; Disease; Disease Resistance; Drug Design; Drug Targeting; Drug resistance; Future; Generations; Goals; Human; In Vitro; Investigation; Machine Learning; Measurement; Measures; Methodology; Methods; Modeling; Molecular; Molecular Biology; Morbidity - disease rate; Mutation; Pharmacology; Probability; Process; Program Sustainability; Protein Dynamics; Protein Engineering; Proteins; Research; Research Project Grants; Resistance; Structure; System; Techniques; Testing; Therapeutic; Therapeutic Intervention; Viral Antibodies; base; biophysical properties; computer studies; data modeling; design; drug candidate; experimental study; improved; in vivo; inhibitor; mortality; neutralizing antibody; new therapeutic target; novel; novel therapeutics; open source; protein protein interaction; protein structure; resistance mutation; response

Project Summary. The determination of three-dimensional protein structures is essential for revealing molecular mechanism of disease processes, and also for structure-based drug design. Concomitantly, technological advances in protein design could revolutionize therapeutic treatment. With these advances, proteins and other molecules can be designed to act on today’s undruggable proteins or tomorrow’s drug-resistant diseases. This proposed MIRA research project focuses on computational and experimental studies of protein structure and design (PS&D). The interlocking goals are to (A) determine protein structure and dynamics in systems of biomedical importance; and (B) design proteins, inhibitors, and their molecular interactions, especially to predict and overcome resistance. We develop novel algorithms in structural molecular biology. To surmount the challenges proposed herein, our algorithms exploit combinatorial optimization, computational geometry and topology, and integrate advanced machine learning techniques. We believe software for PS&D must be I) Open-Source and II) Free software. This is the goal of OSPREY. Thus, we will (C) continue to develop free, open-source algorithms and software not only for challenging problems in the design of proteins and their interactions, but also to determine difficult protein structures and characterize their dynamics. We will use structural data and computational models to understand molecular mechanism and the basis of therapeutic interventions, and perform detailed experimental measurements in vitro and in vivo to confirm, iterate, and improve both our understanding of protein structure and molecular designs. The resulting models of protein structures and dynamics, together with our novel design methodology, will illuminate targets of biochemical and pharmacological significance. We will also advance PS&D by making algorithmic and modeling advances. We will test our methods and predictions by creating designed protein and inhibitor constructs, solving empirical structures, and performing in vitro experiments to measure enhanced biophysical properties on purified components, and in-cell experiments to measure biological efficacy. We will apply our PS&D algorithms to several areas of biomedical importance. We will solve structures of systems under our investigation and further develop the paradigm of protein structure as a continuous probability distribution. A set of synergistic research thrusts is proposed, in which, for example, we will (1) predict future resistance mutations in protein targets of novel drugs, (2) design protein-protein interaction (PPI) inhibitors that target “undruggable” proteins, and (3) use our PS&D methodology to characterize and design antibody:antigen constructs, with the ultimate goal of creating pan-neutralizing antibodies for viral targets. Our sustained program in developing novel computational methods to accurately predict potential drug target mutations in response to early-stage leads should drive the design of more resilient and durable first-generation drug candidates.

项目总结。蛋白质三维结构的确定是揭示分子结构的必要条件